Testing jumps for individual stock Dissertation

Testing offsets for unmarried stock - Dissertation ExampleIn this tryout, emphasis is placed in the comparison of two measures of fluctuation the Bipower Variation which is robust to jump contribution and the Realized Variance which includes the contribution of jumps to the total variance. And based on a high frequency data set of exchange rates, a statistically significant judge of the difference between these two measures of variance provides evidence on the presence of jumps. ... e the joint asymptotic distribution of BVt and RVt as M Where And using It can be seen that there is no coincidence of the event that asymptotically similar to a situation encountered in Hausmans experiment in 1978. Asymptotically, RVt is the most cost-effective cipher of the integrated variance and under the no jumps assumption, BVt is less efficient estimator, therefore the difference of RVt BVt is independent of RVt on the volatility path following of the Hausman (1978) test. According on Hu ang and Tauchen (2005), the power of each absolute bear should be less than 2 to be robust to jumps for the statistics. With the results from Barndorff-Nielsen and Shephard (2006), Andersen, Bollerslev and Diebold in 2004 used time series to test for daily jumps Where on the assumption of no jumps Another test for daily jumps is The results of research conducted by Andersen, Bollerslev, Diebold and Labys (2001, 2003) and Barndorff-Nielsen and Shephard (2004a) depict that the sample performance is improved by basing the test on the logarithm of the variation measures. Therefore the test is And the maximum adjustment The logarithmic adjustment to is And the maximum adjustment is The OP- adaptations of these tests are equivalent to the ratio jump of Barndorff-Nielsen and Shephards results in 2006. A simple t-test on the Relative Jump measure is Where the classical estimate of the variance of the mean Another form is Where a HAC estimator of the variance of the mean. A bootstrap vers ion is Where a bootstrap estimate of the variance of the mean. The Relative Jump can get a bootstrap confidence interval (tlow, tup) for the t test. b) Empirical results The Monte Carlo findings developed z-tests for performing the jumps in a pretty realistic scenario and analyzed on daily